One way to examine the brain of a living person is to take a series of X-rays of the brain, aided by a computer. This is accomplished during a CT scan (computed tomography involves mapping “slices” of the brain by computer). CT scans can show stroke damage, tumors, injuries, and abnormal brain structure. (See Figure 2.12a) A CT scan is often the structural imaging method of choice when there is metal in the body (e.g., a bullet or surgical clips) and useful for imaging possible skull fractures. (See Figure 2.12b.)

Figure 2.12

Mapping Brain Structure

As useful as a CT scan can be for imaging the skull, it doesn’t show very small details within the brain. The relatively newer technique of magnetic resonance imaging, or MRI, provides much more detail (see Figure 2.12c and 2.12d), even allowing doctors to see the effects of very small strokes. The person getting an MRI scan is placed inside a machine that generates a powerful magnetic field to align hydrogen atoms in the brain tissues (these normally spin in a random fashion); then radio pulses are used to make the atoms spin at a particular frequency and direction. The time it takes for the atoms to return to their normal spin allows a computer to create a three-dimensional image of the brain and display “slices” of that image on a screen.

Using MRI as a basis, researchers have developed several techniques that allow us to study other aspects of the brain. MRI spectroscopy allows researchers to estimate the concentration of specific chemicals and neurotransmitters in the brain. Another fascinating technique is called DTI, or diffusion tensor imaging. The brain has two distinct color regions, gray matter, the outer areas consisting largely of neurons with unmyelinated axons, and white matter, the fiber tracts consisting of myelinated axons (the myelin is responsible for the lighter color). DTI uses MRI technology to provide a way to measure connectivity in the brain by imaging these white matter tracts. DTI has been used to investigate many disorders and conditions, including multiple sclerosis, dementia, and schizophrenia (Assaf & Pasternak, 2008; Catani & Thiebaut de Schotten, 2012; Ulmer et al., 2006; Voineskos et al., 2010).

A fairly harmless way to study the activity of the living brain is to record the electrical activity of the cortex just below the skull using a device called an electroencephalograph. The first electroencephalogram (EEG) recording in humans was accomplished in 1924 by Hans Berger (Niedermeyer, 2005). Recording the EEG involves using small metal-disk or sponge-like electrodes placed directly on the scalp, and a special solution to help conduct the electrical signals from the cortex just below. These electrodes are connected to an amplifier and then to a computer to view the information. The resulting electrical output forms waves that indicate many things, such as stages of sleep, seizures, and even the presence of tumors. The EEG can also be used to help determine which areas of the brain are active during various mental tasks that involve memory and attention. EEG activity can be classified according to appearance and frequency, and different waves are associated with different brain activity. For example, alpha waves in the back of the brain are one indication of relaxed wakefulness (seen in bottom two lines in Figure 2.13a). EEG waveforms are covered in more detail in Chapter Four. (See Learning Objective 4.4.)

Figure 2.13

Mapping Brain Function

Another common EEG-based technique focuses on event-related potentials, or ERPs. In ERP studies, multiple presentations of a stimulus are measured during an EEG and then averaged to remove variations in the ongoing brain activity that is normally recorded during the EEG. The result is a measurement of the response of the brain related to the stimulus event itself, or an event-related potential. ERPs allow the study of different stages of cognitive processing. For example, one recent study has investigated differences in brain processing associated with the recognition of facial expression of emotion in individuals with and without schizophrenia (Lee et al., 2010); in other studies ERPs are being studied as a possible method of lie detection (Hu et al., 2013; Rosenfeld et al., 2008). This modality is also being used as part of brain–computer interfaces (BCIs) to assist people like Rick from the chapter opener better communicate and interact with others and the world around them.

The functional neuroimaging methods discussed so far rely on the electrical activity of the brain. Other techniques make use of other indicators of brain activity, including energy consumption or changes in blood oxygen levels (if areas of the brain are active, they are likely using fuel and oxygen). In positron emission tomography (PET), the person is injected with a radioactive glucose (a kind of sugar). The computer detects the activity of the brain cells by looking at which cells are using up the radioactive glucose and projecting the image of that activity onto a monitor. The computer uses colors to indicate different levels of brain activity, with lighter colors often indicating greater activity. (See Figure 2.13b.) With this method, researchers can actually have the person perform different tasks while the computer shows what his or her brain is doing during the task. A related technique is single photon emission computed tomography (SPECT), which measures brain blood flow and uses more easily obtainable radioactive tracers than those used for PET (Bremmer, 2005).

Although traditional MRI scans only show structure, there is a technique called functional MRI (fMRI) in which the computer tracks changes in the oxygen levels of the blood (see Figure 2.13c). By superimposing this picture of where the oxygen goes in the brain over the picture of the brain’s structure, researchers can identify what areas of the brain are active. By combining such images taken over a period of time, a sort of “movie” of the brain’s functioning can be made (Lin et al., 2007). Functional MRIs can give more detail, tend to be clearer than PET scans, and are an incredibly useful tool for research into the workings of the brain. For example, fMRI has been used to demonstrate that older adults with a genetic risk for Alzheimer’s disease show greater activation in brain areas associated with semantic knowledge and word retrieval when compared to older adults without that genetic risk. This finding may one day help clinicians and researchers identify individuals at risk for Alzheimer’s much earlier in the disease process (Wierenga et al., 2010). There is also exciting research suggesting individuals can use fMRI to learn how to regulate their own brain processes. Individuals with schizophrenia were able to use real-time fMRI (rtfMRI) to learn how to control a portion of their brain that assists in recognition of facial emotions, which is a common deficit in schizophrenia (Ruiz et al., 2013).